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            <h1>2D Convolution Layer with Weight Standardization</h1>
<p>This is an implementation of a 2 dimensional convolution layer with <a href="./index.html">Weight Standardization</a></p>

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            <div class="highlight"><pre><span class="lineno">13</span><span></span><span class="kn">import</span> <span class="nn">torch</span>
<span class="lineno">14</span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
<span class="lineno">15</span><span class="kn">from</span> <span class="nn">torch.nn</span> <span class="kn">import</span> <span class="n">functional</span> <span class="k">as</span> <span class="n">F</span>
<span class="lineno">16</span>
<span class="lineno">17</span><span class="kn">from</span> <span class="nn">labml_nn.normalization.weight_standardization</span> <span class="kn">import</span> <span class="n">weight_standardization</span></pre></div>
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            <h2>2D Convolution Layer</h2>
<p>This extends the standard 2D Convolution layer and standardize the weights before the convolution step.</p>

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        <div class='code'>
            <div class="highlight"><pre><span class="lineno">20</span><span class="k">class</span> <span class="nc">Conv2d</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Conv2d</span><span class="p">):</span></pre></div>
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            <div class="highlight"><pre><span class="lineno">26</span>    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span>
<span class="lineno">27</span>                 <span class="n">stride</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="lineno">28</span>                 <span class="n">padding</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span>
<span class="lineno">29</span>                 <span class="n">dilation</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
<span class="lineno">30</span>                 <span class="n">groups</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
<span class="lineno">31</span>                 <span class="n">bias</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
<span class="lineno">32</span>                 <span class="n">padding_mode</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">&#39;zeros&#39;</span><span class="p">,</span>
<span class="lineno">33</span>                 <span class="n">eps</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">1e-5</span><span class="p">):</span>
<span class="lineno">34</span>        <span class="nb">super</span><span class="p">(</span><span class="n">Conv2d</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span>
<span class="lineno">35</span>                                     <span class="n">stride</span><span class="o">=</span><span class="n">stride</span><span class="p">,</span>
<span class="lineno">36</span>                                     <span class="n">padding</span><span class="o">=</span><span class="n">padding</span><span class="p">,</span>
<span class="lineno">37</span>                                     <span class="n">dilation</span><span class="o">=</span><span class="n">dilation</span><span class="p">,</span>
<span class="lineno">38</span>                                     <span class="n">groups</span><span class="o">=</span><span class="n">groups</span><span class="p">,</span>
<span class="lineno">39</span>                                     <span class="n">bias</span><span class="o">=</span><span class="n">bias</span><span class="p">,</span>
<span class="lineno">40</span>                                     <span class="n">padding_mode</span><span class="o">=</span><span class="n">padding_mode</span><span class="p">)</span>
<span class="lineno">41</span>        <span class="bp">self</span><span class="o">.</span><span class="n">eps</span> <span class="o">=</span> <span class="n">eps</span></pre></div>
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        <div class='code'>
            <div class="highlight"><pre><span class="lineno">43</span>    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">):</span>
<span class="lineno">44</span>        <span class="k">return</span> <span class="n">F</span><span class="o">.</span><span class="n">conv2d</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">weight_standardization</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">weight</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">eps</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">bias</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">stride</span><span class="p">,</span>
<span class="lineno">45</span>                        <span class="bp">self</span><span class="o">.</span><span class="n">padding</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">dilation</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">groups</span><span class="p">)</span></pre></div>
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    <div class='section' id='section-4'>
        <div class='docs doc-strings'>
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                <a href='#section-4'>#</a>
            </div>
            <p> A simple test to verify the tensor sizes</p>

        </div>
        <div class='code'>
            <div class="highlight"><pre><span class="lineno">48</span><span class="k">def</span> <span class="nf">_test</span><span class="p">():</span></pre></div>
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        <div class='code'>
            <div class="highlight"><pre><span class="lineno">52</span>    <span class="n">conv2d</span> <span class="o">=</span> <span class="n">Conv2d</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">20</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span>
<span class="lineno">53</span>    <span class="kn">from</span> <span class="nn">labml.logger</span> <span class="kn">import</span> <span class="n">inspect</span>
<span class="lineno">54</span>    <span class="n">inspect</span><span class="p">(</span><span class="n">conv2d</span><span class="o">.</span><span class="n">weight</span><span class="p">)</span>
<span class="lineno">55</span>    <span class="kn">import</span> <span class="nn">torch</span>
<span class="lineno">56</span>    <span class="n">inspect</span><span class="p">(</span><span class="n">conv2d</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">100</span><span class="p">,</span> <span class="mi">100</span><span class="p">)))</span>
<span class="lineno">57</span>
<span class="lineno">58</span>
<span class="lineno">59</span><span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">&#39;__main__&#39;</span><span class="p">:</span>
<span class="lineno">60</span>    <span class="n">_test</span><span class="p">()</span></pre></div>
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